Frontiers in psychology · 2026
The associations between wearable device feedback perception and athletes' training load management behavior: the chain mediating role of physiological data literacy and recovery self-regulation.
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Han Yufeng, Fan Junli
Аннотация
INTRODUCTION: Despite the rapid proliferation of wearable devices in sport, athletes vary considerably in their ability to interpret device-generated physiological feedback, and the psychological pathways linking feedback perception to training load management remain insufficiently understood. This study introduces physiological data literacy (PDL) as a content-specific form of data literacy and examines whether PDL and recovery self-regulation (RSR) sequentially mediate the association between wearable device feedback perception (WFP) and training load management behavior (TLM).
METHODS: Using a cross-sectional design, 357 active athletes (189 males and 168 females; mean age = 22.76 years, SD = 3.68) completed the wearable device feedback perception scale, physiological data literacy scale, recovery self-regulation scale, and training load management behavior scale. Path analysis with bias-corrected bootstrapping (5,000 resamples) was conducted.
RESULTS: WFP showed a positive total association with TLM (β = 0.511). Significant specific indirect associations were observed through PDL (standardized indirect effect = 0.083, 95% CI [0.032, 0.136]) and RSR (standardized indirect effect = 0.085, 95% CI [0.048, 0.128]). A significant sequential indirect association was also observed for the theoretically specified WFP → PDL → RSR → TLM ordering (indirect effect = 0.065, 95% CI [0.040, 0.098]). The direct WFP-TLM association remained significant after inclusion of both mediators. However, the reverse sequential model yielded identical AIC and BIC values.
DISCUSSION: The findings are statistically compatible with a theoretically motivated sequential framework linking WFP, PDL, RSR, and TLM, but the cross-sectional design does not establish temporal precedence or causal direction. PDL represents a conceptually distinct competency that, together with RSR, warrants further examination in longitudinal and intervention research on wearable-supported training.
METHODS: Using a cross-sectional design, 357 active athletes (189 males and 168 females; mean age = 22.76 years, SD = 3.68) completed the wearable device feedback perception scale, physiological data literacy scale, recovery self-regulation scale, and training load management behavior scale. Path analysis with bias-corrected bootstrapping (5,000 resamples) was conducted.
RESULTS: WFP showed a positive total association with TLM (β = 0.511). Significant specific indirect associations were observed through PDL (standardized indirect effect = 0.083, 95% CI [0.032, 0.136]) and RSR (standardized indirect effect = 0.085, 95% CI [0.048, 0.128]). A significant sequential indirect association was also observed for the theoretically specified WFP → PDL → RSR → TLM ordering (indirect effect = 0.065, 95% CI [0.040, 0.098]). The direct WFP-TLM association remained significant after inclusion of both mediators. However, the reverse sequential model yielded identical AIC and BIC values.
DISCUSSION: The findings are statistically compatible with a theoretically motivated sequential framework linking WFP, PDL, RSR, and TLM, but the cross-sectional design does not establish temporal precedence or causal direction. PDL represents a conceptually distinct competency that, together with RSR, warrants further examination in longitudinal and intervention research on wearable-supported training.